Safety and Efficacy Study of Tesofensine/Metoprolol Treatment in Subjects With Type 2 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Efficacy Study of Tesofensine/Metoprolol Treatment in Subjects With Type 2 Diabetes Mellitus (NCT02737891), a randomized phase 2 study. The primary outcome is Effects of Co-administration of Tesofensine/Metoprolol Treatment vs. Placebo on 24-hour Mean Heart Rate.

2. Clinical Question

3. Trial Design

The registry describes a randomized, double-blind, parallel-group, placebo-controlled phase 2 study of tesofensine/metoprolol in subjects with type 2 diabetes mellitus. Its official title also describes a multiple-dose, two-center study. The sponsor was Saniona. The registry lists enrollment of 60 and the study status as completed.

The recorded study dates are start in 2016-04 and primary completion in 2017-01. Participants were assigned to oral tesofensine/metoprolol tablets or matching placebo tablets. The registry record does not report the treatment dose or the allocation procedure beyond stating that allocation was randomized. It does not report the details of how masking was maintained or assessed.

The primary outcome concerned effects of co-administration on 24-hour mean heart rate, measured in beats per minute. The outcome timeframe was baseline to Day 90. Secondary outcomes were change from baseline to end of treatment in HbA1c and body weight, also assessed from baseline to Day 90. The posted outcome summaries list 30 participants in each treatment group for the primary and secondary measures; the registry record does not explain the analysis populations or the handling of participants with missing measurements.

Randomization and masking are design features intended to limit systematic differences between treatment groups and reduce the influence of expectations on assessment. They do not, on their own, establish that all potential sources of bias were controlled. The registry record does not report a detailed protocol, eligibility criteria, treatment adherence, or the original sample-size justification.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Effects of Co-administration of Tesofensine/Metoprolol Treatment vs. Placebo on 24-hour Mean Heart Rate, measured over Baseline to Day 90.

The primary endpoint is 24-hour mean heart rate, expressed in beats per minute. The registry describes telemetry monitoring at baseline, on Day -1 to 1, and at the end of treatment, on Day 90 to 91. Heart rate was measured every minute, and a mean was recorded for every hour. The outcome timeframe is stated as baseline to Day 90.

Using a mean provides a summary of a continuous measure. In this setting, the 24-hour monitoring period is intended to characterize heart rate across a day rather than rely on a single measurement. Averaging hourly recordings can help make the endpoint less dependent on one moment, although it also compresses a sequence of measurements into a summary value. The posted arm summaries give a mean of 67 BPM for tesofensine/metoprolol and 70 BPM for placebo, with standard deviations of 7 and 9, respectively.

The registry record does not describe the exact derivation of the primary analysis variable, including how the baseline and end-of-treatment measurements were combined in the sponsor’s analysis. It is therefore important to distinguish the endpoint’s monitoring procedure from the statistical contrast used to estimate the treatment-group difference. The sponsor reports an ANCOVA analysis of the net mean difference, while the simple recalculation uses posted group summaries and is unadjusted.

7. Results Posted in the Registry

• Tesofensine/Metoprolol: mean 67.00 versus 70.00 on control; difference -3.00 (95% CI -7.08 to 1.08), standardized effect d = -0.37; z-test p = 0.150.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Change From Baseline to End of Treatment in HbA1c

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Tesofensine/Metoprolol: mean 7.30 versus 7.40 on control; difference -0.10 (95% CI -0.43 to 0.23), standardized effect d = -0.15; z-test p = 0.552.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tesofensine/Metoprolol and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline to End of Treatment in Body Weight

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Tesofensine/Metoprolol: mean -3.50 versus -0.30 on control; difference -3.20 (95% CI -11.69 to 5.29), standardized effect d = -0.19; z-test p = 0.460.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tesofensine/Metoprolol and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes assess HbA1c and body weight, adding information about measures distinct from the primary heart-rate endpoint. Across these measures, the sponsor’s adjusted analyses do not produce the same pattern of interval evidence: the HbA1c interval includes zero, while the body-weight interval excludes zero. The simple unadjusted recalculations have intervals that include zero for both. These results do not form a uniformly consistent pattern across analyses.

The secondary outcomes relate to the primary result by describing different dimensions of the intervention comparison, not by independently confirming the heart-rate finding. They cannot resolve the discrepancy between the sponsor’s primary ANCOVA estimate and the unadjusted recalculation. Nor does a result for one outcome determine the result for another, since each endpoint has its own measurement, variability, and analysis.

Secondary results generally carry less weight when there is no reported account of how multiple outcomes were handled. Testing or interpreting several outcomes creates more opportunities for apparently notable results to occur by chance. The registry record does not report a multiplicity adjustment, a hierarchy among the secondary outcomes, or a prespecified strategy for interpreting them. Accordingly, the sponsor-reported secondary estimates should be viewed as additional outcome-specific evidence, not as a basis for overriding the uncertainty and analysis discrepancy in the primary endpoint.

These outcomes are described as changes from baseline to end of treatment, but the registry record does not supply enough detail about analysis populations, missing measurements, or model specification to fully assess their estimation. The distinction between adjusted sponsor analyses and unadjusted summary-statistic recalculations remains relevant across all the posted outcomes.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Change From Baseline to End of Treatment in HbA1c
• Change From Baseline to End of Treatment in Body Weight

9. Statistical Interpretation

10. Statistical Methods Explained

Several statistical ideas help distinguish what the posted results estimate and how much uncertainty remains. The registry reports group means and standard deviations for continuous outcomes, a sponsor ANCOVA analysis, and simple unadjusted recalculations based on the posted summary statistics. These approaches answer related but not identical questions.

What does a mean difference describe?

A mean is the arithmetic average of measured values in a group. A mean difference expresses the separation between two group averages using the outcome’s original units. For the primary endpoint, the units are beats per minute. A negative recalculated difference is consistent with a lower mean in the tesofensine/metoprolol group than in the placebo group, given the comparison direction used in the posted summaries. A group mean difference does not show whether every participant’s value changed in the same direction, and it does not summarize the full shape of the outcome distribution.

The standard deviation describes how dispersed individual measurements are around a group mean. It is not the uncertainty interval for the mean difference. The primary group standard deviations are 7 and 9 BPM. Wider dispersion generally makes a group mean less precise when the sample size is unchanged. The registry record describes continuous outcomes and does not report a count model or an over-dispersion analysis; over-dispersion is therefore not a central issue for interpreting these posted mean comparisons.

Why might ANCOVA differ from an unadjusted comparison?

ANCOVA is a regression-based method that compares groups while accounting for one or more other variables included in the model. In a trial, such a model may use baseline outcome values as covariates, but the registry record does not specify which covariates the sponsor included. Adjustment can change an estimated difference and its standard error. It can also improve precision when the covariates explain variation in the outcome. Because the exact sponsor model is not reported in the registry record, the posted ANCOVA estimates cannot be reconstructed from the group means and standard deviations alone.

The recalculated estimates are simple, unadjusted comparisons based on posted summary statistics. They do not account for baseline values or any other covariates. They are useful as a transparent check against the posted group summaries, but they should not replace the sponsor’s analysis. For the primary endpoint, the discrepancy between the recalculation and the sponsor’s ANCOVA result means the sponsor’s own analysis takes precedence. The record does not state why the estimates differ.

What does a confidence interval communicate?

A confidence interval gives a range of values compatible with the data and the model used to calculate it, under the method’s assumptions. It reflects estimation uncertainty; it is not a range containing a specified proportion of individual participants’ measurements. A narrower interval indicates greater precision for the estimated contrast, while a wider interval leaves more uncertainty about its size and direction. Whether an interval includes zero matters for a difference: zero represents no difference on the scale of that contrast. An interval that includes zero does not establish that the true difference is zero, and an interval that excludes zero does not establish clinical importance.

How should p-values be read?

A p-value describes how unusual the observed result, or a more extreme result, would be under a specified null model and its assumptions. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The recalculated primary p-value is 0.15, while the sponsor reports p = 0.004 for its ANCOVA analysis. Those values relate to different analyses, and the discrepancy is not explained in the registry record. The sponsor’s analysis takes precedence, but the distinction remains important for interpreting the posted results.

The sponsor labels its analyses as superiority analyses. That label describes the stated comparison framework; it does not by itself establish the importance, durability, or broader applicability of a finding. The registry record does not report the prespecified statistical analysis plan or the detailed hypotheses used for each outcome.

What can the summaries not establish?

Aggregate means, standard deviations, confidence intervals, and p-values cannot reveal individual-level response patterns, the effects of missing observations, or the sensitivity of results to alternative analysis choices. The record does not report missing-data methods, analysis populations, model diagnostics, or a full account of covariate adjustment. The result should therefore be read as a comparison under the methods that are reported, with those unreported details kept in view.

11. Confidence Intervals and Precision

Precision concerns how much uncertainty remains around an estimated group difference. The primary unadjusted recalculation gives a mean difference of -3.0 BPM, with a 95% confidence interval from -7.08 to 1.08. Because this interval includes zero, the posted summary statistics do not pin down the direction of the unadjusted difference with high precision. Values across the interval range from a lower mean in the tesofensine/metoprolol group to a small higher mean, under the contrast’s direction and assumptions.

The sponsor’s ANCOVA estimate is -3.8, with a 95% confidence interval from -6.36 to -1.29. This interval excludes zero and is narrower than the interval from the simple recalculation. The results are not identical estimates from the same analysis: the sponsor reports an adjusted ANCOVA result, while the recalculation is unadjusted. Since the discrepancy is true, the sponsor’s own analysis takes precedence. The registry record does not report enough detail to identify why the results differ.

Confidence intervals are about uncertainty in the estimated group contrast, not the spread of individual outcomes. The standard deviations describe variation within groups; the confidence intervals describe precision around an estimated difference. Neither alone establishes whether a difference is important in practice. The registry record does not report a threshold for a clinically meaningful heart-rate difference, so the clinical importance of the estimated values cannot be determined from these results alone.

For the secondary measures, the sponsor-reported intervals differ in whether they include zero, and the unadjusted intervals include zero. That pattern reinforces the need to separate estimates from certainty: a point estimate by itself does not show precision, and a confidence interval does not account for unreported multiplicity or missing-data decisions.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for these continuous outcomes, not total events. They are illustrations based on the observed effect and are not the trial’s original design calculations. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses the stated fraction of the observed effect as the effect to detect.

The 80% power column gives the participants per arm estimated to yield an 80% chance of detecting the chosen effect under those assumptions if that effect is real. The 90% power column expresses the same idea for a 90% chance. These are planning probabilities tied to assumptions; they are not probabilities that a treatment effect is true and do not describe the achieved chance of detecting an effect in this completed trial.

For the primary outcome, planning for 100% of the observed effect gives 114 participants per arm for 80% power and 152 participants per arm for 90% power. Planning for 75% of the observed effect gives 202 participants per arm for 80% power and 270 participants per arm for 90% power. Planning for 50% of the observed effect gives 454 participants per arm for 80% power and 608 participants per arm for 90% power. The figures illustrate the general relationship: smaller effects require more participants to detect under the same planning assumptions.

This is not observed power. The registry record does not report the trial’s original sample-size justification or its own design assumptions. These planning values should not be treated as evidence that the trial was or was not adequately designed, nor as a substitute for interpreting the estimates and confidence intervals.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -3.000; pooled standard deviation σ = 8.062.
2. n = 2 × (1.96 + 0.842)² × 8.062² / -3.000² = 113.4, rounded up to 114 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -3                      # observed difference in means
sigma <- 8.06225774829855                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2737891)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 114 (80% power), 152 (90% power)
 75% of observed effect: n per arm = 202 (80% power), 270 (90% power)
 50% of observed effect: n per arm = 454 (80% power), 608 (90% power)
power.t.test: 114.3 
Simulated power at n = 114 per arm: 0.800 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

For the primary endpoint, the sponsor reports ANCOVA with a net mean difference of -3.8, a 95% confidence interval from -6.36 to -1.29, and p = 0.004. The simple recalculation from the posted group means and standard deviations is -3.0, with a 95% confidence interval from -7.08 to 1.08 and an unadjusted p-value of 0.15. The recalculation is not the sponsor’s adjusted analysis and does not reproduce it.

The estimates differ, and the sponsor-reported interval excludes zero while the recalculated interval includes zero. Because the discrepancy is present, the sponsor’s own analysis takes precedence when reporting the trial’s primary result. That precedence does not explain the discrepancy or make the methods interchangeable. The registry record does not specify the covariates used in ANCOVA or otherwise explain why the estimates differ.

The sponsor also reports ANCOVA analyses for the secondary endpoints. Their results should likewise be distinguished from the simple unadjusted recalculations. The registry record does not provide enough methodological detail to reconstruct those adjusted analyses from the posted summaries. The sponsor’s estimates are the trial-reported analyses, while the recalculations are limited checks based on group-level summaries.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary outcome and two secondary outcomes, but does not report how multiplicity was addressed. Multiplicity arises when several outcomes or hypotheses are examined: even if each analysis is conducted appropriately, the chance of at least one apparently unusual result can increase across a family of tests. A prespecified hierarchy, adjustment procedure, or clearly stated confirmatory status can help readers understand how multiple results were intended to be interpreted. Those details are not reported in the registry record.

The sponsor labels the reported analyses as superiority analyses, but the record does not include a full statistical analysis plan. It does not report whether the secondary outcomes were confirmatory or exploratory, whether any adjustments were planned, or how the timing of analyses was determined. The trial’s original sample-size assumptions and justification are also not reported in the registry record; the planning illustrations based on observed effects are not substitutes for that information.

Missing-data handling and analysis populations are likewise not reported in the registry record. The outcome summaries list 30 participants in each arm, but the record does not specify whether those values represent all randomized participants, participants with available outcome measurements, or another analysis population. It does not describe withdrawals, missing endpoint values, imputation, or sensitivity analyses. Without this information, it is not possible to assess whether missing observations could have influenced the estimates.

The registry record also does not explain the discrepancy between the sponsor’s ANCOVA results and the simple unadjusted recalculations. Details such as model covariates, outcome derivation, and analysis population could clarify the comparison, but those specifics cannot be inferred. These gaps do not invalidate the posted estimates; they limit how fully the analysis can be independently evaluated.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: cholelithiasis (3.3%).

The posted safety summaries report serious adverse events affecting 0 participants in the tesofensine/metoprolol group and 1 participant in the placebo group. Other adverse events affected 20 participants in the tesofensine/metoprolol group and 12 in the placebo group. No deaths are reported in either group. The registry lists cholelithiasis at 3.3% among the top serious adverse event terms.

These are descriptive counts for this trial and should be read in the context of the group sizes and the study’s limited enrollment. Counts do not establish that an intervention caused or prevented an event. The registry record does not report event-level details, severity beyond the serious-event classification, timing, duration, or a comparative statistical analysis of safety outcomes. A zero count for deaths or serious adverse events in a group does not establish that the risk is absent. The reported adverse-event summaries also do not provide a complete account of all possible risks.

17. What the Result Does, and Does Not, Mean

The posted results describe a comparison between tesofensine/metoprolol and placebo in a randomized, double-blind phase 2 study involving people with type 2 diabetes. The primary measure was 24-hour mean heart rate. The sponsor’s adjusted ANCOVA analysis reports a net difference with a 95% confidence interval that excludes zero, while the simple unadjusted recalculation has a wider interval that includes zero. The registry record does not explain why these analyses differ, so both the result and that limitation matter.

The result does not establish the clinical importance of the estimated heart-rate difference. The registry record does not report a threshold for a meaningful difference, and a group average does not predict an individual participant’s response. The primary outcome also does not, by itself, answer questions about longer-term outcomes or other aspects of health.

The secondary HbA1c and body-weight outcomes provide additional comparisons, but their interpretation is limited by differing patterns between adjusted and unadjusted analyses and by the absence of reported multiplicity methods. Their results should not be treated as independent confirmation of the primary finding.

The record describes the study as completed and reports safety counts, but does not supply detailed information about missing data, analysis populations, treatment dose, or the original sample-size justification. These omissions restrict assessment of the robustness and generalizability of the estimates. The posted results should therefore be understood as evidence from this particular trial and its reported analyses, not as a definitive answer to broader treatment questions.

18. Why This Trial Matters Statistically

This trial illustrates why statistical interpretation requires more than reading a point estimate or p-value. The sponsor’s adjusted primary estimate and the simple recalculation from posted summaries differ in both magnitude and interval relation to zero. Recognizing that distinction prevents an unadjusted reconstruction from being mistaken for the trial’s own analysis, while retaining transparency about the discrepancy.

It also shows the value of separating within-group variability from uncertainty in a comparison. The standard deviations describe dispersion in each group, whereas confidence intervals characterize uncertainty around the estimated difference. These quantities answer different questions, and neither alone establishes clinical importance.

The contrast between the primary and secondary outcome analyses further illustrates why multiple outcomes require a prespecified interpretive framework. The registry record does not report multiplicity methods, so secondary results have to be treated cautiously rather than selectively elevated. Finally, planning illustrations based on observed effects are not the original design rationale and are not observed power. Together, these issues make clear how reporting detail affects the strength and limits of conclusions that can be drawn from a clinical trial record.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations specific to this record constrain interpretation. The primary outcome has a discrepancy between the sponsor’s ANCOVA result and the simple unadjusted recalculation. The sponsor analysis takes precedence, but the registry record does not explain the difference or report the model covariates needed to reproduce the adjusted estimate.

The record does not report the original sample-size justification, the prespecified statistical analysis plan, missing-data methods, or the analysis populations. It also does not explain whether outcome summaries include every randomized participant or only those with available measurements. These gaps prevent a full assessment of the robustness of the estimates.

The registry does not report the intervention dose, detailed eligibility criteria, adherence, or a multiplicity strategy for the primary and secondary outcomes. The secondary endpoints show different patterns across adjusted and unadjusted analyses, and their interpretation is further limited by the lack of reported multiplicity handling. The posted safety counts are descriptive and do not include detailed event timing or a comparative safety analysis.

Finally, the study is identified as phase 2, with enrollment of 60 and a completed status. The results therefore describe this trial and its reported follow-up, with no basis in the registry record for assuming that the estimates apply to other populations, settings, or longer periods.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Safety and Efficacy Study of Tesofensine/Metoprolol Treatment in Subjects With Type 2 Diabetes Mellitus — NCT02737891.
• Registry record last updated 2020-05-14; status last verified 2020-05.
• Results first posted 2020-05-14.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT02737891 is a completed, randomized, double-blind, parallel-group, placebo-controlled phase 2 study sponsored by Saniona. It studied oral tesofensine/metoprolol versus matching placebo in subjects with type 2 diabetes mellitus. The primary endpoint was 24-hour mean heart rate from baseline to Day 90; HbA1c and body weight were secondary outcomes.

The sponsor reports an ANCOVA primary estimate of -3.8 BPM, with a 95% confidence interval from -6.36 to -1.29 and p = 0.004. A simple unadjusted recalculation differs, with an estimate of -3.0 BPM and a 95% confidence interval from -7.08 to 1.08. Because of this discrepancy, the sponsor’s own analysis takes precedence. The registry record does not explain the difference or report several details needed to fully assess the analyses, including multiplicity and missing-data methods.